Important Dates & Reminders

Monday, May 22 2023: Registration for Fall begins

Monday, May 29 2023: No classes - Memorial Day

Saturday, June 3 2023: Spring Classes End

Monday, June 5 2023: Spring Examinations Begin

Please send any upcoming news and events to news@cs.northwestern.edu to be included in future bulletins and/or on the CS website.

Events:

Data Science for All / Women | Deadline May 21st

"If We Want AI to be Interpretable, We Need to Measure Interpretability", Jordan Boyd-Graber | May 22nd 12PM

"A Career in AI Research, Application and Education", Anand Rao | May 23rd 12PM

Bagel Friday | May 26th 9:30AM

End of Year Awards Celebration | June 1st 1PM

Annual Poster Session for Research in Sustainability and Resilience | June 6th 3PM

News

Abstract:
AI tools are ubiquitous, but most users treat it as a black box: a handy tool that suggests purchases, flags spam, or autocompletes text. While researchers have presented explanations for making AI less of a black box, a lack of metrics make it hard to optimize explicitly for interpretability. Thus, I propose two metrics for interpretability suitable for unsupervised and supervised AI methods. For unsupervised topic models, I discuss our proposed "intruder" interpretability metric, how it contradicts the previous evaluation metric for topic models (perplexity), and discuss its uptake in the community over the last decade. For supervised question answering approaches, I show how human-computer cooperation can be measured and directly optimized by a multi-armed bandit approach to learn what kinds of explanations help specific users. I will then briefly discuss how similar setups can help users navigate information-rich domains like fact checking, translation, and web search.

Biography:
Jordan Boyd-Graber is an associate professor in the University of Maryland's Computer Science Department, iSchool, UMIACS, and Language Science Center. He generally works on how humans can interact with AI tools, starting first with topic models, then translation, then negotiation, and most recently question answering. He and his students have won "best of" awards at NIPS (2009, 2015), NAACL (2016), and CoNLL (2015). Jordan also won the British Computing Society's 2015 Karen Spärk Jones Award and a 2017 NSF CAREER award.

Abstract:
I will discuss my career journey from academics to research to industry and back, with a focus on my early work in symbolic AI, Belief-Desire-Intention architectures, and building multi-agent systems that later led to applying large-scale agent-based simulations in the financial sector, healthcare and auto sectors. Woven through this journey has been my passion for innovation, thought leadership, teaching and mentoring. I am retiring from PwC this summer, and am interested in returning to academia as a next career step - helping the next generation of practitioners to prepare and succeed.

Biography:
Dr. Anand S. Rao is the Global Artificial Intelligence Leader for PwC. He is also the leader of PwC’s AI and Emerging Technology practice.  With over 35 years of industry and consulting experience, Anand leads a team of practitioners who advise C-level executives and implement advanced analytics and AI-based solutions on a variety of strategic, operational, and ethical use cases. With his PhD and research career in Artificial Intelligence and his subsequent experience in management consulting he brings business domain knowledge, software engineer expertise, and statistical expertise to generate unique insights into the practice of ‘data science’.  
Prior to joining management consulting, Anand was the Chief Research Scientist at the Australian Artificial Intelligence Institute. He received his PhD from University of Sydney (with a University Postgraduate Research Award-UPRA) in 1988 and an MBA (with Award of Distinction) from Melbourne Business School in 1997. Anand has also co-edited four books on Intelligent Agents and has published over fifty papers in Computer Science and Artificial Intelligence in major journals, conferences, and workshops.  
He has received widespread recognition for his extraordinary contributions in the field of consulting and Artificial Intelligence Research.  He has received the Most Influential Paper Award for the Decade in 2007 from the Autonomous Agents & Multi-Agent Systems organization for his contribution on the Belief-Desire-Intention Architecture; MBA Award of Distinction from Melbourne Business School, 1997 and University Postgraduate Research Award (UPRA) from University of Sydney, 1985; Distinguished Alumnus Award from Birla Institute of Technology and Science, Pilani, India; He was recognized as one of Top 50 Data & Analytics professionals in USA and Canada by Corinium; one of Top 50 professionals in InsureTech; one of Top 25 Technology Leaders in Consulting; and has won a number of awards for his academic and business papers.
Anand is an Adjunct Professor in BITS Pilani’s APPCAIR AI Center. He also serves on the Advisory Board of Oxford University’s Institute for Ethics in AI, World Economic Forum’s Global AI Council, OECD’s Network of Experts on AI (ONE), OECD’s AI Compute initiative, Advisory Board of Northwestern’s MBAi program,  Responsible AI Institute, Nordic AI Institute, and International Congress for the Governance of AI.

Northwestern Department of Computer Science

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